One of the biggest issues in online education is attrition.  “Student retention is a noteworthy issue for higher education institutions and is closely tied to accountability,” write Melanie Shaw of Northcentral University, Scott Burrus of University of Phoenix, and Karen Ferguson of Colorado State University-Global Campus.  In an article in the fall 2016 issue of the Online Journal of Distance Learning Administration, the trio details research they conducted to determine predictors for online higher education student attrition.

Looking at the research

Initial research shows that online institutions compare favorably with on-ground institutions when it comes to student attrition.  Citing 2015 research from U.S. News and World Report, the authors found that “most studies show that student attrition rates at online institutions are 3 percent to 5 percent higher than those of traditional institutions.”

According to 2004 work by Dupin-Bryant, these factors are related to student retention: “class rank, grade point average (GPA), previous online experience, technology training, and internet training.” The need to assess these types of factors led to the researchers using SmarterMeasure (“a tool used by many institutions to evaluate the attributes, skills, and knowledge students possess that may contribute to their overall success in degree completion”) for their study.

Study results

The authors gathered data about students in different domains for study.  These included:

  • Individual attributes – motivation, procrastination, willingness to ask for help, etc.
  • Life factors – availability of time, support from family and employers, finances, etc.
  • Learning styles – based on the multiple intelligences model
  • Technical competency – skills using technology
  • Technical knowledge
  • Typing speed and accuracy
  • On-screen reading rate and recall

Results then helped answer the three main research questions.

What factors can institutions use to identify at-risk students?

To answer this question, the researchers looked at the statistical significance of “various life factors, learning styles, personal attributes, technology competencies, technology knowledge, typing speed, typing accuracy, and reading ability on the overall likelihood of withdrawal or dismissal.”  They discovered that physical and verbal learning styles as well as a tendency toward procrastination all increased the likelihood of attrition.

What learning readiness factors are associated with online student retention?

For the second research question the researchers looked at the same factors to see if any decreased the likelihood of attrition.  They found that having clear reasons for pursuing a degree, good typing speed, and readiness skills all decreased the likelihood of attrition.

Additionally, the researchers discovered several factors that had no effect on attrition:

  • Life factors – the place students devote to studying, the resources students have available like technology, and the time students planned to devote to their coursework did not have an effect
  • Learning style – aural, logical, social, solitary, and visual student learning styles did not have an effect
  • Personal attributes – academic, help seeking, locus of control, persistence, and time management factors did not have an effect
  • Technological – technical competency, technology knowledge, typing accuracy, and reading (words per minute) did not have an effect

What strategies can be used to promote student retention once at-risk students are identified?

To test this question, researchers investigated the impact on outreach to “students with low readiness scores on any of the statistically significant at-risk factors.” Students were grouped by similar scores and demographics. The control group received no outreach efforts.  The experimental group received intervention as follows, the researchers write:

“The experimental group received an outreach call prior to the first day of the first course.  During that call, a representative from the school shared school-specific information and resources to support the students’ areas of low readiness. In addition, the representative demonstrated how to access the library, academic success center, time management support program; and provided students with guidance on how to schedule time with an academic coach. The conversations were followed up with emails that included links to all of the support resources available.”

The results were dramatic:

 “After six months, the experimental group had an 11 percent greater level of retention than the control group.  Additionally, there were observable differences in the performance of the two groups.  The control group had more dropped courses, more failing grades and course withdrawals, and tended to have more students who were two or more assignments behind the course due dates.  The experimental group showed greater persistence, fewer failing grades and course withdrawals, and submitted more on-time assignments.”


The research led to several important recommendations for online educators:

  1. Students be able to articulate their motivation for engaging in their program early in the enrollment process. SmarterMeasure data included significant findings for students who had a clear understanding of why they were enrolling in a degree program. These students had lower attrition than students who could not articulate reasons for enrolling. As such, effort should be made to assist the student in specifying educational goals and the rationale for enrolling in the first place.
  2. Institutions should help students develop college readiness skills. Because of the influence of readiness on student success, institutions should provide resources for and remediation to students who do not possess fundamental readiness skills.
  3. Institutions should promote students’ technology readiness. While many technology factors were not indicators of student retention, typing speed was. Typing speed may be correlated with higher levels of computer fluency, so more research is needed relative to this success factor.
  4. Institutions should address the needs of students with various learning styles. If students identify as having a physical or verbal learning style preference, greater levels of support may need to be provided to ensure online success.
  5. Faculty should develop a mentoring skill set to best support student progress. While this recommendation did not arise directly from the results of this study, researchers clearly connect effective teaching with student success (Bégin & Gérard, 2013; Salter-Dvorak, 2014; Willis & Carmichael, 2011). As such, efforts should be taken to promote faculty mentoring skills.
  6. A quality student-faculty relationship and healthy communication should be fostered. The literature (Bitzer, 2011; Salter-Dvorak, 2014; Spaulding & Rockinson-Szapkiw, 2011; Stallone, 2011) and the experimental aspect of this research study demonstrated that proactive faculty, who are attuned to student needs are more likely to intervene to promote retention.
  7. Students should be provided with regular feedback to help them master content knowledge (Hedge, 2013).  While this study did not address faculty feedback, because of the prominence of this factor as an influencer of student success in the literature, this recommendation should be heeded.

The original article appeared in the Fall 2016 issue of the Online Journal of Distance Learning Administration. (  It is summarized here with the permission of Karen Ferguson.

Jennifer Lorenzetti is editor of Academic Leader and a member of the Leadership in Higher Education Conference advisory board. She is a writer, speaker, higher education consultant, and the owner of Hilltop Communications. 

Reprinted from Distance Education Report, 20.21 (2016): 1, 2, 6. © Magna Publications. All rights reserved.